Abstract Females aged 15-24 years consistently have the highest rates of Chlamydia trachomatis (CT) that is implicated in 40-50% of salpingitis, a primary cause of infertility. Biologic vulnerability to CT is often attributed to cervical epithelial immaturity, but is likely much more complex and lies in the relationships among cervical topography, immunity, and the cervicovaginal microbiome (CVM) and its functional state. Data suggest that CVMs dominated by anaerobes and L. iners are linked to increased CT risk, whereas L. crispatus-dominant CVMs appear protective. Once infected, immune responses are diverse, ranging from minimal response to over- active response with the risk of tissue damage and sequelae. Pre-existing inflammation may predispose to over-active responses. In vivo studies of biologic vulnerability have been difficult since prospective data is rare. We have the unique opportunity to utilize a biorepository from the HPV Natural History Cohort (R37CA51323; PI Moscicki), a 25 year prospective study of 1500 women aged 13-24 years at entry, which has over 10 million datapoints and 200,000 stored biologic samples collected at 4-6 month intervals. CT testing was routinely performed annually and anytime the patient had symptoms. Our Aims are to examine: 1) associations between the CVM and its functional state, and risk for CT acquisition, 2) whether the CVM and cervical maturation status are synergistic in influencing the risk for CT; 3) whether the CVM and its functional state prior to infection predicts the level of inflammatory response during infection. We hypothesize that L. crispatus- dominant CVMs lower the risk of CT acquisition via metabolomic profiles that include higher levels of organic acids, glucose consumption, and little inflammation. CVMs dominated by diverse anaerobes or L. iners raise the risk with lower levels of organic acids and higher levels of inflammation. Larger areas of cervical immaturity are more likely to harbor harmful CVMs. Pro-inflammatory states found pre-infection will be associated with destructive inflammatory responses during infection, leading to loss of epithelial integrity. Aims 1 & 2 will use a nested case-control design (100 cases, 200 controls), where selected visits reflect 3 time points per woman (2 CT(-) and 1 CT(+) visits for incident cases, 3 CT(-) visits for controls). Biologic factors measured at the CT(-) visits for cases will be compared to those for controls who represent a similar at-risk population. Aim 3 will focus on the 100 cases. Biologic measures at the pre-CT visit will be tested as predictors of the immune response to incident CT. Data will include: colpophotos for cervical maturity; cervical saline washes for CVMs, metabolomics, cytokines, proteomics; and detailed interviews for patient history. Data analyses will examine this highly multivariate longitudinal data. Statistical and bioinformatic approaches will include a combination of mixed effects longitudinal models, weighted gene co-expression network analysis, microbiome diversity evaluation, principal components analysis and repeated measures logistic regression models for associations between the biologic measures and CT acquisition and inflammation.